This study analyzes gender identification in Brazilian Portuguese using Amazon reviews drawn from ten product categories. Nine models were evaluated: three classical classifiers (Logistic Regression, Random Forest, and SVM), a multilingual BERT, and five LLMs (ChatGPT 4o, ChatGPT 3.5, DeepSeek, Sabia3, and Sabiazinho). Experiments show that BERT achieved the best performance (macro-F1 = 0.634), outperforming ChatGPT 4o and Logistic Regression by less than one percentage point. Reviews authored by women reach an average F1 of 0.654—four points higher than those by men. Performance also varies by domain: books and automotive are easier, whereas baby and pets are more challenging.
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